Autor segons l'article: Picart-Armada, Sergio; Fernandez-Albert, Francesc; Vinaixa, Maria; Rodriguez, Miguel A; Aivio, Suvi; Stracker, Travis H; Yanes, Oscar; Perera-Lluna, Alexandre
Departament: Enginyeria Electrònica, Elèctrica i Automàtica
Autor/s de la URV: Rodríguez Chacón, Matilde / Vinaixa Crevillent, Maria / Yanes Torrado, Óscar
Paraules clau: Tool Pathways Lc/ms
Resum: Metabolomics experiments identify metabolites whose abundance varies as the conditions under study change. Pathway enrichment tools help in the identification of key metabolic processes and in building a plausible biological explanation for these variations. Although several methods are available for pathway enrichment using experimental evidence, metabolomics does not yet have a comprehensive overview in a network layout at multiple molecular levels. We propose a novel pathway enrichment procedure for analysing summary metabolomics data based on sub-network analysis in a graph representation of a reference database. Relevant entries are extracted from the database according to statistical measures over a null diffusive process that accounts for network topology and pathway crosstalk. Entries are reported as a sub-pathway network, including not only pathways, but also modules, enzymes, reactions and possibly other compound candidates for further analyses. This provides a richer biological context, suitable for generating new study hypotheses and potential enzymatic targets. Using this method, we report results from cells depleted for an uncharacterised mitochondrial gene using GC and LC-MS data and employing KEGG as a knowledge base. Partial validation is provided with NMR-based tracking of 13C glucose labelling of these cells.
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Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
ISSN: 19326203
Adreça de correu electrònic de l'autor: maria.vinaixa@urv.cat oscar.yanes@urv.cat matilde.rodriguez@urv.cat maria.vinaixa@urv.cat
Identificador de l'autor: 0000-0001-9804-0171 0000-0003-3695-7157 0000-0001-9804-0171
Data d'alta del registre: 2024-10-12
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0189012
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Plos One. 12 (12): 467-
Referència de l'ítem segons les normes APA: Picart-Armada, Sergio; Fernandez-Albert, Francesc; Vinaixa, Maria; Rodriguez, Miguel A; Aivio, Suvi; Stracker, Travis H; Yanes, Oscar; Perera-Lluna, A (2017). Null diffusion-based enrichment for metabolomics data. Plos One, 12(12), 467-. DOI: 10.1371/journal.pone.0189012
DOI de l'article: 10.1371/journal.pone.0189012
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2017
Tipus de publicació: Journal Publications
Repositori URV